Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations421570
Missing cells1422431
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory86.0 MiB
Average record size in memory214.0 B

Variable types

Numeric13
DateTime1
Boolean1
Categorical1

Alerts

MarkDown1 is highly overall correlated with MarkDown4 and 1 other fieldsHigh correlation
MarkDown4 is highly overall correlated with MarkDown1High correlation
MarkDown5 is highly overall correlated with MarkDown1 and 1 other fieldsHigh correlation
Size is highly overall correlated with MarkDown5 and 1 other fieldsHigh correlation
Store is highly overall correlated with TypeHigh correlation
Type is highly overall correlated with Size and 1 other fieldsHigh correlation
IsHoliday is highly imbalanced (63.3%) Imbalance
MarkDown1 has 270889 (64.3%) missing values Missing
MarkDown2 has 310322 (73.6%) missing values Missing
MarkDown3 has 284479 (67.5%) missing values Missing
MarkDown4 has 286603 (68.0%) missing values Missing
MarkDown5 has 270138 (64.1%) missing values Missing

Reproduction

Analysis started2025-08-23 19:07:00.043150
Analysis finished2025-08-23 19:07:54.319918
Duration54.28 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Store
Real number (ℝ)

High correlation 

Distinct45
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.200546
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:07:54.807788image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median22
Q333
95-th percentile43
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation12.785297
Coefficient of variation (CV)0.57590014
Kurtosis-1.1465028
Mean22.200546
Median Absolute Deviation (MAD)11
Skewness0.077762502
Sum9359084
Variance163.46383
MonotonicityIncreasing
2025-08-23T22:07:55.081316image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
13 10474
 
2.5%
10 10315
 
2.4%
4 10272
 
2.4%
1 10244
 
2.4%
2 10238
 
2.4%
24 10228
 
2.4%
27 10225
 
2.4%
34 10224
 
2.4%
20 10214
 
2.4%
6 10211
 
2.4%
Other values (35) 318925
75.7%
ValueCountFrequency (%)
1 10244
2.4%
2 10238
2.4%
3 9036
2.1%
4 10272
2.4%
5 8999
2.1%
6 10211
2.4%
7 9762
2.3%
8 9895
2.3%
9 8867
2.1%
10 10315
2.4%
ValueCountFrequency (%)
45 9637
2.3%
44 7169
1.7%
43 6751
1.6%
42 6953
1.6%
41 10088
2.4%
40 10017
2.4%
39 9878
2.3%
38 7362
1.7%
37 7206
1.7%
36 6222
1.5%

Dept
Real number (ℝ)

Distinct81
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.260317
Minimum1
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:07:55.316268image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q118
median37
Q374
95-th percentile95
Maximum99
Range98
Interquartile range (IQR)56

Descriptive statistics

Standard deviation30.492054
Coefficient of variation (CV)0.68892534
Kurtosis-1.2155706
Mean44.260317
Median Absolute Deviation (MAD)23
Skewness0.35822319
Sum18658822
Variance929.76536
MonotonicityNot monotonic
2025-08-23T22:07:55.715856image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6435
 
1.5%
16 6435
 
1.5%
92 6435
 
1.5%
38 6435
 
1.5%
40 6435
 
1.5%
2 6435
 
1.5%
82 6435
 
1.5%
46 6435
 
1.5%
95 6435
 
1.5%
81 6435
 
1.5%
Other values (71) 357220
84.7%
ValueCountFrequency (%)
1 6435
1.5%
2 6435
1.5%
3 6435
1.5%
4 6435
1.5%
5 6347
1.5%
6 5986
1.4%
7 6435
1.5%
8 6435
1.5%
9 6354
1.5%
10 6435
1.5%
ValueCountFrequency (%)
99 862
 
0.2%
98 5836
1.4%
97 6278
1.5%
96 4854
1.2%
95 6435
1.5%
94 5685
1.3%
93 5913
1.4%
92 6435
1.5%
91 6435
1.5%
90 6435
1.5%

Date
Date

Distinct143
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.2 MiB
Minimum2010-02-05 00:00:00
Maximum2012-10-26 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-08-23T22:07:55.994662image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:56.210949image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

IsHoliday
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size411.8 KiB
False
391909 
True
 
29661
ValueCountFrequency (%)
False 391909
93.0%
True 29661
 
7.0%
2025-08-23T22:07:56.403074image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Temperature
Real number (ℝ)

Distinct3528
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.090059
Minimum-2.06
Maximum100.14
Zeros0
Zeros (%)0.0%
Negative69
Negative (%)< 0.1%
Memory size3.2 MiB
2025-08-23T22:07:56.622768image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-2.06
5-th percentile27.31
Q146.68
median62.09
Q374.28
95-th percentile87.27
Maximum100.14
Range102.2
Interquartile range (IQR)27.6

Descriptive statistics

Standard deviation18.447931
Coefficient of variation (CV)0.30700471
Kurtosis-0.63592198
Mean60.090059
Median Absolute Deviation (MAD)13.63
Skewness-0.32140415
Sum25332166
Variance340.32616
MonotonicityNot monotonic
2025-08-23T22:07:56.960840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50.43 709
 
0.2%
67.87 646
 
0.2%
72.62 594
 
0.1%
76.67 583
 
0.1%
70.28 563
 
0.1%
76.03 555
 
0.1%
50.56 544
 
0.1%
64.05 542
 
0.1%
64.21 519
 
0.1%
50.81 487
 
0.1%
Other values (3518) 415828
98.6%
ValueCountFrequency (%)
-2.06 69
< 0.1%
5.54 68
< 0.1%
6.23 69
< 0.1%
7.46 69
< 0.1%
9.51 70
< 0.1%
9.55 69
< 0.1%
10.09 66
< 0.1%
10.11 68
< 0.1%
10.24 69
< 0.1%
10.53 72
< 0.1%
ValueCountFrequency (%)
100.14 44
 
< 0.1%
100.07 46
 
< 0.1%
99.66 48
 
< 0.1%
99.22 185
< 0.1%
99.2 46
 
< 0.1%
98.43 43
 
< 0.1%
98.15 47
 
< 0.1%
97.66 42
 
< 0.1%
97.6 48
 
< 0.1%
97.18 187
< 0.1%

Fuel_Price
Real number (ℝ)

Distinct892
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3610265
Minimum2.472
Maximum4.468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:07:57.245613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2.472
5-th percentile2.653
Q12.933
median3.452
Q33.738
95-th percentile4.029
Maximum4.468
Range1.996
Interquartile range (IQR)0.805

Descriptive statistics

Standard deviation0.45851454
Coefficient of variation (CV)0.13642098
Kurtosis-1.1854045
Mean3.3610265
Median Absolute Deviation (MAD)0.375
Skewness-0.1049015
Sum1416908
Variance0.21023558
MonotonicityNot monotonic
2025-08-23T22:07:57.498389image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.638 2548
 
0.6%
3.63 2164
 
0.5%
2.771 1917
 
0.5%
3.891 1856
 
0.4%
3.594 1796
 
0.4%
3.524 1793
 
0.4%
3.523 1792
 
0.4%
2.72 1790
 
0.4%
3.666 1778
 
0.4%
2.78 1656
 
0.4%
Other values (882) 402480
95.5%
ValueCountFrequency (%)
2.472 38
 
< 0.1%
2.513 45
 
< 0.1%
2.514 906
0.2%
2.52 39
 
< 0.1%
2.533 42
 
< 0.1%
2.539 37
 
< 0.1%
2.54 147
 
< 0.1%
2.542 45
 
< 0.1%
2.545 38
 
< 0.1%
2.548 902
0.2%
ValueCountFrequency (%)
4.468 368
0.1%
4.449 358
0.1%
4.308 168
< 0.1%
4.301 360
0.1%
4.294 363
0.1%
4.293 192
< 0.1%
4.288 172
< 0.1%
4.282 173
< 0.1%
4.277 357
0.1%
4.273 366
0.1%

MarkDown1
Real number (ℝ)

High correlation  Missing 

Distinct2277
Distinct (%)1.5%
Missing270889
Missing (%)64.3%
Infinite0
Infinite (%)0.0%
Mean7246.4202
Minimum0.27
Maximum88646.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:07:57.746884image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.27
5-th percentile149.19
Q12240.27
median5347.45
Q39210.9
95-th percentile21801.35
Maximum88646.76
Range88646.49
Interquartile range (IQR)6970.63

Descriptive statistics

Standard deviation8291.2213
Coefficient of variation (CV)1.1441817
Kurtosis17.606263
Mean7246.4202
Median Absolute Deviation (MAD)3430.74
Skewness3.3418447
Sum1.0918978 × 109
Variance68744351
MonotonicityNot monotonic
2025-08-23T22:07:57.991101image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.5 102
 
< 0.1%
460.73 102
 
< 0.1%
175.64 93
 
< 0.1%
1282.42 75
 
< 0.1%
9264.48 75
 
< 0.1%
686.24 75
 
< 0.1%
5924.71 75
 
< 0.1%
1483.17 75
 
< 0.1%
3124.45 74
 
< 0.1%
6809.96 74
 
< 0.1%
Other values (2267) 149861
35.5%
(Missing) 270889
64.3%
ValueCountFrequency (%)
0.27 51
< 0.1%
0.5 49
< 0.1%
1.5 102
< 0.1%
1.94 50
< 0.1%
2.12 52
< 0.1%
2.4 49
< 0.1%
2.42 50
< 0.1%
2.43 51
< 0.1%
2.8 50
< 0.1%
2.91 51
< 0.1%
ValueCountFrequency (%)
88646.76 68
< 0.1%
78124.5 70
< 0.1%
75149.79 73
< 0.1%
65021.23 73
< 0.1%
62567.6 66
< 0.1%
62172.73 72
< 0.1%
60740.64 70
< 0.1%
60394.73 72
< 0.1%
58928.52 72
< 0.1%
56917.7 71
< 0.1%

MarkDown2
Real number (ℝ)

Missing 

Distinct1499
Distinct (%)1.3%
Missing310322
Missing (%)73.6%
Infinite0
Infinite (%)0.0%
Mean3334.6286
Minimum-265.76
Maximum104519.54
Zeros207
Zeros (%)< 0.1%
Negative1311
Negative (%)0.3%
Memory size3.2 MiB
2025-08-23T22:07:58.195450image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-265.76
5-th percentile1.95
Q141.6
median192
Q31926.94
95-th percentile16497.47
Maximum104519.54
Range104785.3
Interquartile range (IQR)1885.34

Descriptive statistics

Standard deviation9475.3573
Coefficient of variation (CV)2.841503
Kurtosis37.589561
Mean3334.6286
Median Absolute Deviation (MAD)184.73
Skewness5.4412612
Sum3.7097076 × 108
Variance89782396
MonotonicityNot monotonic
2025-08-23T22:07:58.575940image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.91 539
 
0.1%
3 493
 
0.1%
0.5 485
 
0.1%
1.5 471
 
0.1%
4 367
 
0.1%
6 365
 
0.1%
7.64 354
 
0.1%
3.82 353
 
0.1%
19 345
 
0.1%
5.73 345
 
0.1%
Other values (1489) 107131
 
25.4%
(Missing) 310322
73.6%
ValueCountFrequency (%)
-265.76 71
< 0.1%
-192 72
< 0.1%
-20 72
< 0.1%
-10.98 60
< 0.1%
-10.5 143
< 0.1%
-9.98 68
< 0.1%
-9.94 62
< 0.1%
-7.6 69
< 0.1%
-7.01 69
< 0.1%
-6.69 69
< 0.1%
ValueCountFrequency (%)
104519.54 72
< 0.1%
97740.99 73
< 0.1%
92523.94 73
< 0.1%
89121.94 74
< 0.1%
82881.16 73
< 0.1%
72413.71 72
< 0.1%
70574.85 71
< 0.1%
58804.91 69
< 0.1%
58046.41 71
< 0.1%
56106.2 72
< 0.1%

MarkDown3
Real number (ℝ)

Missing 

Distinct1662
Distinct (%)1.2%
Missing284479
Missing (%)67.5%
Infinite0
Infinite (%)0.0%
Mean1439.4214
Minimum-29.1
Maximum141630.61
Zeros67
Zeros (%)< 0.1%
Negative257
Negative (%)0.1%
Memory size3.2 MiB
2025-08-23T22:07:58.886178image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-29.1
5-th percentile0.65
Q15.08
median24.6
Q3103.99
95-th percentile1059.9
Maximum141630.61
Range141659.71
Interquartile range (IQR)98.91

Descriptive statistics

Standard deviation9623.0783
Coefficient of variation (CV)6.6853796
Kurtosis77.687772
Mean1439.4214
Median Absolute Deviation (MAD)22.6
Skewness8.399453
Sum1.9733172 × 108
Variance92603636
MonotonicityNot monotonic
2025-08-23T22:07:59.289293image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 754
 
0.2%
6 710
 
0.2%
2 660
 
0.2%
1 611
 
0.1%
0.22 487
 
0.1%
0.5 463
 
0.1%
0.01 444
 
0.1%
4 439
 
0.1%
3.2 379
 
0.1%
1.98 363
 
0.1%
Other values (1652) 131781
31.3%
(Missing) 284479
67.5%
ValueCountFrequency (%)
-29.1 72
 
< 0.1%
-1 70
 
< 0.1%
-0.87 46
 
< 0.1%
-0.2 69
 
< 0.1%
0 67
 
< 0.1%
0.01 444
0.1%
0.02 124
 
< 0.1%
0.04 241
0.1%
0.05 71
 
< 0.1%
0.06 205
< 0.1%
ValueCountFrequency (%)
141630.61 74
< 0.1%
109030.75 75
< 0.1%
103991.94 72
< 0.1%
101378.79 73
< 0.1%
89402.64 71
< 0.1%
88805.58 72
< 0.1%
83340.33 74
< 0.1%
83192.81 74
< 0.1%
79621.2 72
< 0.1%
77451.26 73
< 0.1%

MarkDown4
Real number (ℝ)

High correlation  Missing 

Distinct1944
Distinct (%)1.4%
Missing286603
Missing (%)68.0%
Infinite0
Infinite (%)0.0%
Mean3383.1683
Minimum0.22
Maximum67474.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:07:59.590174image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.22
5-th percentile28.76
Q1504.22
median1481.31
Q33595.04
95-th percentile12645.96
Maximum67474.85
Range67474.63
Interquartile range (IQR)3090.82

Descriptive statistics

Standard deviation6292.384
Coefficient of variation (CV)1.8599087
Kurtosis29.996815
Mean3383.1683
Median Absolute Deviation (MAD)1167.55
Skewness4.8475
Sum4.5661607 × 108
Variance39594097
MonotonicityNot monotonic
2025-08-23T22:07:59.859275image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9 280
 
0.1%
4 200
 
< 0.1%
2 197
 
< 0.1%
3 146
 
< 0.1%
47 143
 
< 0.1%
67.72 142
 
< 0.1%
657.56 141
 
< 0.1%
17 141
 
< 0.1%
8 140
 
< 0.1%
1330.36 140
 
< 0.1%
Other values (1934) 133297
31.6%
(Missing) 286603
68.0%
ValueCountFrequency (%)
0.22 57
 
< 0.1%
0.41 52
 
< 0.1%
0.46 48
 
< 0.1%
0.78 52
 
< 0.1%
0.87 49
 
< 0.1%
0.92 45
 
< 0.1%
1.5 55
 
< 0.1%
1.88 48
 
< 0.1%
1.98 44
 
< 0.1%
2 197
< 0.1%
ValueCountFrequency (%)
67474.85 72
< 0.1%
57817.56 74
< 0.1%
57815.43 68
< 0.1%
53603.99 72
< 0.1%
52739.02 72
< 0.1%
48403.53 70
< 0.1%
48159.86 73
< 0.1%
48086.64 72
< 0.1%
47452.43 73
< 0.1%
46238.28 71
< 0.1%

MarkDown5
Real number (ℝ)

High correlation  Missing 

Distinct2293
Distinct (%)1.5%
Missing270138
Missing (%)64.1%
Infinite0
Infinite (%)0.0%
Mean4628.9751
Minimum135.16
Maximum108519.28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:08:00.166207image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum135.16
5-th percentile715.52
Q11878.44
median3359.45
Q35563.8
95-th percentile11269.24
Maximum108519.28
Range108384.12
Interquartile range (IQR)3685.36

Descriptive statistics

Standard deviation5962.8875
Coefficient of variation (CV)1.2881658
Kurtosis107.84927
Mean4628.9751
Median Absolute Deviation (MAD)1702.47
Skewness8.1699095
Sum7.0097495 × 108
Variance35556027
MonotonicityNot monotonic
2025-08-23T22:08:00.616092image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2743.18 136
 
< 0.1%
1064.56 120
 
< 0.1%
9083.54 75
 
< 0.1%
3567.03 75
 
< 0.1%
3557.67 75
 
< 0.1%
20371.02 75
 
< 0.1%
4180.29 75
 
< 0.1%
1773.53 74
 
< 0.1%
3932.94 74
 
< 0.1%
4464.45 74
 
< 0.1%
Other values (2283) 150579
35.7%
(Missing) 270138
64.1%
ValueCountFrequency (%)
135.16 65
< 0.1%
153.04 47
< 0.1%
153.9 49
< 0.1%
164.08 52
< 0.1%
170.64 69
< 0.1%
171.76 71
< 0.1%
180.07 64
< 0.1%
212.75 50
< 0.1%
224.86 50
< 0.1%
227.12 48
< 0.1%
ValueCountFrequency (%)
108519.28 68
< 0.1%
105223.11 70
< 0.1%
85851.87 68
< 0.1%
63005.58 69
< 0.1%
58068.14 69
< 0.1%
57029.78 68
< 0.1%
53212.72 70
< 0.1%
37581.27 70
< 0.1%
36430.33 71
< 0.1%
36360.42 72
< 0.1%

CPI
Real number (ℝ)

Distinct2145
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean171.20195
Minimum126.064
Maximum227.23281
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:08:00.871173image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum126.064
5-th percentile126.49626
Q1132.02267
median182.31878
Q3212.41699
95-th percentile221.94156
Maximum227.23281
Range101.16881
Interquartile range (IQR)80.394326

Descriptive statistics

Standard deviation39.159276
Coefficient of variation (CV)0.22873149
Kurtosis-1.8297144
Mean171.20195
Median Absolute Deviation (MAD)41.434863
Skewness0.085219285
Sum72173605
Variance1533.4489
MonotonicityNot monotonic
2025-08-23T22:08:01.187369image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.8555333 711
 
0.2%
131.1083333 708
 
0.2%
129.8459667 707
 
0.2%
130.3849032 706
 
0.2%
130.6457931 706
 
0.2%
131.0756667 706
 
0.2%
130.683 706
 
0.2%
130.4546207 705
 
0.2%
130.7196333 705
 
0.2%
130.737871 704
 
0.2%
Other values (2135) 414506
98.3%
ValueCountFrequency (%)
126.064 678
0.2%
126.0766452 679
0.2%
126.0854516 675
0.2%
126.0892903 682
0.2%
126.1019355 686
0.2%
126.1069032 681
0.2%
126.1119032 682
0.2%
126.114 687
0.2%
126.1145806 689
0.2%
126.1266 683
0.2%
ValueCountFrequency (%)
227.2328068 63
< 0.1%
227.214288 62
< 0.1%
227.1693919 63
< 0.1%
227.0369359 70
< 0.1%
227.0184166 69
< 0.1%
226.9873637 134
< 0.1%
226.9735448 69
< 0.1%
226.9688442 134
< 0.1%
226.9662325 63
< 0.1%
226.9239785 135
< 0.1%

Unemployment
Real number (ℝ)

Distinct349
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9602887
Minimum3.879
Maximum14.313
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:08:01.512399image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.879
5-th percentile5.326
Q16.891
median7.866
Q38.572
95-th percentile12.187
Maximum14.313
Range10.434
Interquartile range (IQR)1.681

Descriptive statistics

Standard deviation1.863296
Coefficient of variation (CV)0.23407393
Kurtosis2.7312166
Mean7.9602887
Median Absolute Deviation (MAD)0.858
Skewness1.1837426
Sum3355818.9
Variance3.4718721
MonotonicityNot monotonic
2025-08-23T22:08:01.787738image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.099 5152
 
1.2%
8.163 3636
 
0.9%
7.852 3614
 
0.9%
7.343 3416
 
0.8%
7.057 3414
 
0.8%
7.931 3400
 
0.8%
7.441 3397
 
0.8%
6.565 3370
 
0.8%
8.2 3361
 
0.8%
6.891 3360
 
0.8%
Other values (339) 385450
91.4%
ValueCountFrequency (%)
3.879 287
 
0.1%
4.077 938
0.2%
4.125 1831
0.4%
4.145 562
 
0.1%
4.156 1815
0.4%
4.261 1829
0.4%
4.308 935
0.2%
4.42 1855
0.4%
4.584 1988
0.5%
4.607 935
0.2%
ValueCountFrequency (%)
14.313 2636
0.6%
14.18 2423
0.6%
14.099 2441
0.6%
14.021 2263
0.5%
13.975 1529
0.4%
13.736 2464
0.6%
13.503 2661
0.6%
12.89 2491
0.6%
12.187 2507
0.6%
11.627 2502
0.6%

Type
Categorical

High correlation 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.1 MiB
A
215478 
B
163495 
C
42597 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters421570
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowA
5th rowA

Common Values

ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Length

2025-08-23T22:08:02.018586image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-08-23T22:08:02.215725image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
a 215478
51.1%
b 163495
38.8%
c 42597
 
10.1%

Most occurring characters

ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 421570
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 421570
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 421570
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 215478
51.1%
B 163495
38.8%
C 42597
 
10.1%

Size
Real number (ℝ)

High correlation 

Distinct40
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136727.92
Minimum34875
Maximum219622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 MiB
2025-08-23T22:08:02.460980image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum34875
5-th percentile39690
Q193638
median140167
Q3202505
95-th percentile206302
Maximum219622
Range184747
Interquartile range (IQR)108867

Descriptive statistics

Standard deviation60980.583
Coefficient of variation (CV)0.44599951
Kurtosis-1.2063459
Mean136727.92
Median Absolute Deviation (MAD)62140
Skewness-0.32584977
Sum5.7640387 × 1010
Variance3.7186315 × 109
MonotonicityNot monotonic
2025-08-23T22:08:02.708310image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
39690 20802
 
4.9%
39910 20597
 
4.9%
203819 20376
 
4.8%
219622 10474
 
2.5%
126512 10315
 
2.4%
205863 10272
 
2.4%
151315 10244
 
2.4%
202307 10238
 
2.4%
204184 10225
 
2.4%
158114 10224
 
2.4%
Other values (30) 287803
68.3%
ValueCountFrequency (%)
34875 8999
2.1%
37392 9036
2.1%
39690 20802
4.9%
39910 20597
4.9%
41062 6751
 
1.6%
42988 7156
 
1.7%
57197 9443
2.2%
70713 9762
2.3%
93188 9864
2.3%
93638 9455
2.2%
ValueCountFrequency (%)
219622 10474
2.5%
207499 10062
2.4%
206302 10113
2.4%
205863 10272
2.4%
204184 10225
2.4%
203819 20376
4.8%
203750 10142
2.4%
203742 10214
2.4%
203007 10202
2.4%
202505 10211
2.4%

Weekly_Sales
Real number (ℝ)

Distinct359464
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15981.258
Minimum-4988.94
Maximum693099.36
Zeros73
Zeros (%)< 0.1%
Negative1285
Negative (%)0.3%
Memory size3.2 MiB
2025-08-23T22:08:03.015275image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-4988.94
5-th percentile59.9745
Q12079.65
median7612.03
Q320205.853
95-th percentile61201.951
Maximum693099.36
Range698088.3
Interquartile range (IQR)18126.202

Descriptive statistics

Standard deviation22711.184
Coefficient of variation (CV)1.4211136
Kurtosis21.49129
Mean15981.258
Median Absolute Deviation (MAD)6747.645
Skewness3.2620082
Sum6.737219 × 109
Variance5.1579786 × 108
MonotonicityNot monotonic
2025-08-23T22:08:03.422855image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 353
 
0.1%
5 289
 
0.1%
20 232
 
0.1%
15 215
 
0.1%
12 175
 
< 0.1%
1 169
 
< 0.1%
10.47 167
 
< 0.1%
11.97 154
 
< 0.1%
2 148
 
< 0.1%
7 146
 
< 0.1%
Other values (359454) 419522
99.5%
ValueCountFrequency (%)
-4988.94 1
 
< 0.1%
-3924 1
 
< 0.1%
-1750 1
 
< 0.1%
-1699 1
 
< 0.1%
-1321.48 1
 
< 0.1%
-1098 3
< 0.1%
-1008.96 1
 
< 0.1%
-898 1
 
< 0.1%
-863 1
 
< 0.1%
-798 4
< 0.1%
ValueCountFrequency (%)
693099.36 1
< 0.1%
649770.18 1
< 0.1%
630999.19 1
< 0.1%
627962.93 1
< 0.1%
474330.1 1
< 0.1%
422306.25 1
< 0.1%
420586.57 1
< 0.1%
406988.63 1
< 0.1%
404245.03 1
< 0.1%
393705.2 1
< 0.1%

Interactions

2025-08-23T22:07:48.175062image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:12.282039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:15.179272image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:18.402864image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:21.280704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:24.891995image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:27.710417image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:30.347792image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:33.279427image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:36.007030image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:38.841755image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:42.038924image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:45.157758image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:48.486583image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:12.565930image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:15.396108image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:18.625609image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:21.543735image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:25.143059image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:27.886379image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:30.573822image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:33.477154image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:36.186267image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:39.208791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:42.288227image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:45.377988image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:48.734764image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:12.841537image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:15.625985image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:18.834476image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:21.926607image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:25.359173image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:28.066678image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:30.795642image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:33.700004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:36.373658image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:39.472079image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:42.542258image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:45.593081image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:48.991523image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:13.102913image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:15.882711image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:19.078634image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:22.165072image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:25.580783image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:28.282800image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:31.032362image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:33.919925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:36.579021image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:39.721094image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:42.808344image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:45.819277image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:49.244621image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:13.321409image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:16.147337image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:19.281563image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:22.386591image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:25.807075image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:28.469527image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:31.265810image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:34.153791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:36.783477image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:39.942219image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:43.044947image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:46.041270image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:49.400107image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:13.476704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:16.430227image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:19.469528image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:22.746207image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:26.011915image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:28.647657image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:31.446232image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:34.339121image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:37.005802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:40.113694image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:43.368875image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:46.201412image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:49.580457image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:13.663247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:16.671981image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:19.650048image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:22.943295image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:26.247101image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:28.837259image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:31.653988image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:34.552034image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:37.248427image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:40.312935image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:43.553419image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:46.383289image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:49.773126image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:13.869920image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:16.929392image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:19.842484image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:23.239007image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:26.469622image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:29.066159image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:31.856701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:34.756891image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:37.463736image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:40.518142image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:43.773205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:46.583257image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:49.963748image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:14.054138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:17.203710image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:20.043243image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:23.500378image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:26.677603image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:29.299506image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:32.078180image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:34.994647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:37.694615image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:40.712808image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:43.964917image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:46.775840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:50.234060image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:14.270157image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:17.421529image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:20.270014image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:23.792938image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:26.876295image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:29.508491image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:32.399602image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:35.196925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:37.897611image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:40.966109image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:44.196906image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:47.083786image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:50.494858image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:14.466384image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:17.639424image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:20.514538image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:24.049035image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:27.104908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:29.685899image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:32.586010image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:35.387016image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:38.090559image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:41.221467image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:44.416726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:47.341327image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:50.768514image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:14.673404image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:17.861076image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:20.744588image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:24.311261image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:27.300156image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:29.877666image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:32.787017image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:35.582468image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:38.350053image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:41.472983image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:44.619112image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:47.596074image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:51.064343image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:14.930273image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:18.131027image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:21.022589image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:24.597600image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:27.507415image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:30.142920image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:33.057906image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:35.787041image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:38.559460image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:41.763663image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:44.881191image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-08-23T22:07:47.876956image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2025-08-23T22:08:03.720021image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
CPIDeptFuel_PriceIsHolidayMarkDown1MarkDown2MarkDown3MarkDown4MarkDown5SizeStoreTemperatureTypeUnemploymentWeekly_Sales
CPI1.000-0.009-0.0410.012-0.017-0.099-0.111-0.0630.021-0.005-0.2300.1730.183-0.383-0.023
Dept-0.0091.0000.0030.0000.0020.0030.0060.0070.0060.0110.0140.0010.0800.006-0.014
Fuel_Price-0.0410.0031.0000.1360.163-0.155-0.2180.073-0.0880.0040.0740.1280.088-0.0600.002
IsHoliday0.0120.0000.1361.0000.0570.3590.4580.1150.0600.0000.0000.1860.0000.0350.031
MarkDown1-0.0170.0020.1630.0571.0000.2060.1540.7590.5080.499-0.2120.0020.1720.0640.192
MarkDown2-0.0990.003-0.1550.3590.2061.0000.0660.1160.1520.1490.009-0.4620.0660.0600.032
MarkDown3-0.1110.006-0.2180.4580.1540.0661.0000.0020.2440.300-0.065-0.2570.0650.0430.135
MarkDown4-0.0630.0070.0730.1150.7590.1160.0021.0000.3800.288-0.0390.1410.0660.0380.112
MarkDown50.0210.006-0.0880.0600.5080.1520.2440.3801.0000.579-0.156-0.0710.094-0.0190.208
Size-0.0050.0110.0040.0000.4990.1490.3000.2880.5791.000-0.160-0.0430.851-0.0660.290
Store-0.2300.0140.0740.000-0.2120.009-0.065-0.039-0.156-0.1601.000-0.0570.5380.295-0.102
Temperature0.1730.0010.1280.1860.002-0.462-0.2570.141-0.071-0.043-0.0571.0000.1230.030-0.020
Type0.1830.0800.0880.0000.1720.0660.0650.0660.0940.8510.5380.1231.0000.1810.089
Unemployment-0.3830.006-0.0600.0350.0640.0600.0430.038-0.019-0.0660.2950.0300.1811.000-0.016
Weekly_Sales-0.023-0.0140.0020.0310.1920.0320.1350.1120.2080.290-0.102-0.0200.089-0.0161.000

Missing values

2025-08-23T22:07:51.413020image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2025-08-23T22:07:52.306247image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-08-23T22:07:53.686480image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

StoreDeptDateIsHolidayTemperatureFuel_PriceMarkDown1MarkDown2MarkDown3MarkDown4MarkDown5CPIUnemploymentTypeSizeWeekly_Sales
0112010-02-05False42.312.572NaNNaNNaNNaNNaN211.0963588.106A15131524924.50
1112010-02-12True38.512.548NaNNaNNaNNaNNaN211.2421708.106A15131546039.49
2112010-02-19False39.932.514NaNNaNNaNNaNNaN211.2891438.106A15131541595.55
3112010-02-26False46.632.561NaNNaNNaNNaNNaN211.3196438.106A15131519403.54
4112010-03-05False46.502.625NaNNaNNaNNaNNaN211.3501438.106A15131521827.90
5112010-03-12False57.792.667NaNNaNNaNNaNNaN211.3806438.106A15131521043.39
6112010-03-19False54.582.720NaNNaNNaNNaNNaN211.2156358.106A15131522136.64
7112010-03-26False51.452.732NaNNaNNaNNaNNaN211.0180428.106A15131526229.21
8112010-04-02False62.272.719NaNNaNNaNNaNNaN210.8204507.808A15131557258.43
9112010-04-09False65.862.770NaNNaNNaNNaNNaN210.6228577.808A15131542960.91
StoreDeptDateIsHolidayTemperatureFuel_PriceMarkDown1MarkDown2MarkDown3MarkDown4MarkDown5CPIUnemploymentTypeSizeWeekly_Sales
42156045982012-08-24False72.623.8347936.2058.3822.005518.072291.97191.3448878.684B118221415.40
42156145982012-08-31False75.093.86723641.306.0092.936988.313992.13191.4612818.684B118221346.04
42156245982012-09-07True75.703.91111024.4512.8052.631854.772055.70191.5776768.684B118221352.44
42156345982012-09-14False67.873.94811407.95NaN4.303421.725268.92191.6998508.684B118221605.96
42156445982012-09-21False65.324.0388452.2092.2863.242376.388670.40191.8567048.684B118221467.30
42156545982012-09-28False64.883.9974556.6120.641.501601.013288.25192.0135588.684B118221508.37
42156645982012-10-05False64.893.9855046.74NaN18.822253.432340.01192.1704128.667B118221628.10
42156745982012-10-12False54.474.0001956.28NaN7.89599.323990.54192.3272658.667B1182211061.02
42156845982012-10-19False56.473.9692004.02NaN3.18437.731537.49192.3308548.667B118221760.01
42156945982012-10-26False58.853.8824018.9158.08100.00211.94858.33192.3088998.667B1182211076.80